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Displaying posts with tag: mongodb (reset)
Fast index create

What is a fast way to create secondary indexes for a write-optimized database engine?

Back in the day the only way to create a secondary index for InnoDB was via incremental maintenance. Insert, update and delete statements would maintain secondary indexes as needed. The CREATE INDEX command for a secondary index would make a copy of the table, define all indexes (primary and secondary) and then scan the source table in PK order and insert rows from the scan into the copy table while maintaining secondary indexes after each insert.  In most cases the result from this is a secondary index subject to changes in a random sequence. That means the secondary index is fully fragmented immediately after index create and there was no way to defragment a secondary index. Fragmentation is bad as it means you are wasting space and using about 1.5X the space for the index compared to the index without fragmentation.

Today …

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MySQL shell prompt vs MongoDB shell prompt

Recently Todd Farmer shared an interesting story about the mysql command line prompt in MySQL 5.7: how it was changed to provide more context and why the change was finally reverted. This made me think that after using the command line client for MongoDB for awhile, I would love seeing a much more modern mysql shell prompt. Here are a few examples of what a modern command line client can do.

Add dynamic information to the prompt

If you use replication with MongoDB, you have probably noticed a nice feature of the prompt: it is replication aware. What I mean is that for a standalone instance, the prompt is simply:


When you configure this instance to be the primary of a replica set named RS, the prompt automatically becomes:


and for secondaries, you will see:

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Choosing a good sharding key in MongoDB (and MySQL)

MongoDB 3.0 was recently released. Instead of focusing on what’s new – that is so easy to find, let’s rather talk about something that has not changed a lot since the early MongoDB days. This topic is sharding and most specifically: how to choose a good sharding key. Note that most of the discussion will also apply to MySQL, so if you are more interested in sharding than in MongoDB, it could still be worth reading.

When do you want to shard?

In general sharding is recommended with MongoDB as soon as any of these conditions is met:

  • #1: A single server can no longer handle the write workload.
  • #2: The working set no longer fits in memory.
  • #3: The dataset is too large to easily fit in a single server.

Note that #1 and #2 are by far the most common reason why people need sharding. Also note that in the MySQL world, #2 does not imply that you need sharding.

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Advanced JSON for MySQL

What is JSON

JSON is an text based, human readable format for transmitting data between systems, for serializing objects and for storing document store data for documents that have different attributes/schema for each document. Popular document store databases use JSON (and the related BSON) for storing and transmitting data.

Problems with JSON in MySQL

It is difficult to inter-operate between MySQL and MongoDB (or other document databases) because JSON has traditionally been very difficult to work with. Up until recently, JSON is just a TEXT document. I said up until recently, so what has changed? The biggest thing is that there are new JSON UDF by Sveta Smirnova, which are part of the MySQL 5.7 Labs releases. Currently the JSON UDF are up to version 0.0.4. While these new UDF are a welcome edition to the MySQL database, they don’t solve the really tough …

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Bad Benchmarketing and the Bar Chart

Technical conferences are flooded with visual [mis]representations of a particular product's performance, compression, cost effectiveness, micro-transactions per flux-capacitor, or whatever two-axis comparison someone dreams up. Lets be honest, benchmarketers like to believe we all suffer from innumeracy.

The Merriam-Webster dictionary defines innumeracy as follows:
innumeracy (noun): marked by an ignorance of mathematics and the scientific approach Mark Callaghan has been a long time advocate of explaining benchmark results, but that's not the point of the bar chart. Oh no, the bar chart only exists to catch your eye and …

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Increasing Cloud Database Efficiency – Like Crows in a Closet

In Mo’ Data, Mo’ Problems, we explored the paradox that “Big Data” projects pose to organizations and how Tokutek is taking an innovative approach to solving those problems. In this post, we’re going to talk about another hot topic in IT, “The Cloud,” and how enterprises undertaking Cloud efforts often struggle with idea of “problem trading.” Also, for some reason, databases are just given a pass as traditionally “noisy neighbors” and that there is nothing that can be done about it. Lets take a look at why we disagree.

With the birth of the information age came a coupling of business and IT. Increasingly strategic business projects and objectives were reliant on information infrastructure to provide information storage and retrieval instead of paper and filing cabinets. This was the dawn of the database and what gave rise to companies like Oracle, Sybase and MySQL. With the appearance of true Enterprise Grade …

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Real-time data loading from Oracle and MySQL to data warehouses, analytics

Analyzing transactional data is becoming increasingly common, especially as the data sizes and complexity increase and transactional stores are no longer to keep pace with the ever-increasing storage. Although there are many techniques available for loading data, getting effective data in real-time into your data warehouse store is a more difficult problem.In this webinar-on-demand we showcase

How to benchmark MongoDB

There are generally three components to any benchmark project:

  1. Create the benchmark application
  2. Execute it
  3. Publish your results

I assume many people think they want to run more benchmarks but give up since step 2 is extremely consuming as you expand the number of different configurations/scenarios.

I'm hoping that this blog post will encourage more people to dive-in and participate, as I'll be sharing the bash script I used to test the various compression options coming in the MongoDB 3.0 storage engines. It enabled me to run a few different tests against 8 different configurations, recording insertion speed and size-on-disk for each one.

If you're into this sort of thing, please read on and provide any feedback or improvements you can think of. …

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Storage efficiency

Storage efficiency is a big deal. I have learned a lot about read, write and space amplification over the past few years. Tiered storage has been a part of my work life via flashcache, but tiered storage for an LSM doesn't require flashcache. This is going to get interesting. We have more choices for SSD at a variety of price points based on write endurance and performance.  We have write-optimized database engines (RocksDB, Tokutek, WiredTiger) arriving for OLTP workloads. We can use this with commodity hardware and open-source DBMS solutions like MySQL and …

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Severalnines News & Tools: New DevOps Guide Webinar, Load Balancing for MySQL Replay and More..

February 4, 2015 By Severalnines Check Out Our Latest Technical Resources for MySQL, MariaDB & MongoDB Clusters


Like every month, we have created new content and tools for you; here is a summary of what we’ve published. Please do check it out and let us know if you have any comments or feedback.


New Live Technical Webinars


A DevOps Guide to Database Infrastructure Automation for eCommerce

Tuesday, February 17th


Infrastructure automation isn’t easy, but it’s not rocket science either, says Riaan Nolan. Automation is a worthwhile investment for retailers serious about eCommerce, but deciding on which …

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Showing entries 61 to 70 of 271
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